RTK paddy field weeding unmanned ship based on ROS2 robot operation system and control method

Abstract

The invention relates to an RTK paddy field weeding unmanned ship based on an ROS2 robot operation system and a control method. The unmanned ship comprises a ship body, an RTK positioning and orientation module, a weeding execution module, a power driving module, an ROS2 distributed control module, a power module and an emergency remote control module. The ROS2 distributed control module comprises a navigation control node, a motion control node, a GNSS (Global Navigation Satellite System) data acquisition node and a dual-channel fault-tolerant detection system; the navigation control node generates a reference path according to a preset operation area; the motion control node is used for optimizing a control instruction of the double-duct propeller; the GNSS data acquisition node is used for acquiring positioning data in real time, packaging the data into a standard message format and publishing the data to a system bus for other subscription nodes to acquire in real time; the dual-channel fault-tolerant detection system comprises an external link monitoring node and a health monitoring node; the RTK paddy field weeding unmanned ship can break through the technical bottlenecks of traditional paddy field weeding equipment in the aspects of shallow water adaptability, positioning precision and crop protection.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural intelligent equipment, and in particular to an RTK paddy field weeding unmanned boat and a control method based on the ROS2 robot operating system. Background Art

[0002] With the advancement of global agricultural modernization, the application of intelligent and automated technologies in agriculture is becoming increasingly widespread. Against this backdrop, unmanned driving technology, as a crucial component of modern agricultural development, has demonstrated tremendous potential in farmland management. In particular, in specialized agricultural environments such as rice cultivation, drones and automated agricultural machinery are widely used for operations such as plant protection, fertilization, and irrigation. However, the application of these existing technologies to paddy field management faces numerous challenges, particularly in terms of operational accuracy, environmental adaptability, and efficiency. Innovative solutions are urgently needed to address these shortcomings.

[0003] Drones, as an important intelligent agricultural tool, can quickly cover wide areas, but their application is limited in specialized scenarios such as paddy fields. Drones are subject to certain restrictions on their flight altitude, payload capacity, and flight time. Furthermore, during spraying operations, their inherent wind patterns often affect the spraying effect, resulting in uneven distribution of pesticides and fertilizers. Furthermore, the slippery nature and unstable climatic conditions of paddy fields limit the stability and accuracy of drone operations. In contrast, while self-propelled agricultural machinery can perform ground operations, their larger size makes them prone to crushing seedlings during operation, causing crop damage. Particularly in paddy fields, self-propelled agricultural machinery has poor adaptability, and its operating accuracy falls far short of the demands of modern precision agriculture.

[0004] Therefore, finding a new field management tool, particularly one that can operate flexibly in paddy fields without negatively impacting crops, has become a pressing challenge in the agricultural sector. Unmanned boats, as lightweight and flexible operating platforms, are gradually becoming a powerful alternative to traditional agricultural machinery. Unmanned boats are highly adaptable and can operate efficiently in shallow waters while avoiding the risk of crushing rice seedlings, making them particularly well-suited to the specific environment of rice paddies. However, most existing unmanned boats are designed primarily for open water environments such as the ocean, making them difficult to directly apply to the shallow, enclosed environments of paddy fields. Summary of the Invention

[0005] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide an RTK paddy field weeding unmanned boat based on the ROS2 robot operating system. The RTK paddy field weeding unmanned boat breaks through the technical bottlenecks of traditional paddy field weeding equipment in shallow water adaptability, positioning accuracy and crop protection.

[0006] The second object of the present invention is to provide a control method for an RTK paddy field weeding unmanned boat based on the ROS2 robot operating system.

[0007] The technical solution of the present invention to solve the above technical problems is:

[0008] An RTK paddy field weeding unmanned boat based on the ROS2 robot operating system is characterized by comprising a hull, an RTK positioning and orientation module, a weeding execution module, a power drive module, a ROS2 distributed control module, a power supply module and an emergency remote control module, wherein:

[0009] The RTK positioning and orientation module includes a ground base station and a mobile station installed on the hull, wherein the ground base station is used to receive satellite signals and send differential data to the mobile station using a data radio; the mobile station processes the received differential data, outputs positioning data and heading angle information, and transmits it to the ROS2 distributed control module;

[0010] The power drive module includes a dual-ducted propeller and an electronic speed governor provided on the hull, wherein the electronic speed governor controls the steering of the hull by adjusting the speed difference between the ducted fans on both sides of the dual-ducted propeller and dynamically adjusts the steering response in combination with real-time positioning data;

[0011] The ROS2 distributed control module includes a navigation control node, a motion control node, a GNSS data acquisition node and a dual-channel fault-tolerant detection system, wherein the navigation control node is used to generate a reference path according to a preset operating area; the motion control node is used to optimize the control instructions of the dual-duct propulsion system; the GNSS data acquisition node is used to obtain positioning data in real time, and encapsulate the data into a standard message format through the ROS2 topic communication mechanism, and publish it to the system bus for other subscribing nodes to obtain in real time; the dual-channel fault-tolerant detection system includes an external link monitoring node and a health monitoring node, wherein the external link monitoring node is used to verify the frame header and frame tail of the SBUS protocol in real time, trigger the out-of-control protection when 5 consecutive frames of invalid data are detected, and send an emergency stop command to the hardware enable end of the power drive module; the health monitoring node is used to verify the loading status of all functional nodes when the system starts, detect the survival status of each functional node at a frequency of 10Hz during operation, and immediately stop the current operation task when any functional node is offline;

[0012] The power supply module is used to supply power to each functional module.

[0013] Preferably, the hull is made of aluminum alloy and adopts a flat-bottom streamlined design.

[0014] Preferably, the ground base station receives satellite signals through a high-gain antenna and a multi-frequency GNSS module, and uses a data transmission radio to send differential data to the mobile station.

[0015] Preferably, the mobile station is deployed in the cabin of the hull, constructs a space baseline vector through a double helix antenna, and uses space vector solution technology to solve the received differential data, outputs positioning data and heading angle information in real time, and transmits it to the ROS2 distributed control module through serial communication.

[0016] Preferably, the navigation control node uses a line-of-sight guidance algorithm to generate a reference path.

[0017] Preferably, the motion control node performs real-time rolling optimization on the motion state of the unmanned ship based on a model-predictive motion control algorithm, and calculates the thrust values ​​required by the ducted fans on both sides of the dual-ducted propulsion system.

[0018] Preferably, the weeding execution module is composed of a plurality of chains; the plurality of chains are arranged in parallel along the width direction of the hull; one end of each chain is fixed to the stern through a connector, and a counterweight is provided at the other end.

[0019] Preferably, the power supply module includes a power supply module, a voltage conversion module and a protection module.

[0020] Preferably, the emergency remote control module includes a handheld remote control and an SBUS receiver, wherein the handheld remote control is equipped with a three-position switch corresponding to manual mode, automatic mode and emergency stop mode; the SBUS receiver is used to receive remote control signals in real time.

[0021] A control method for an RTK paddy field weeding unmanned boat based on the ROS2 robot operating system includes the following steps:

[0022] The ground base station receives satellite signals and uses a data transmission radio to send differential data to the mobile station; the mobile station processes the received differential data, outputs positioning data and heading angle information, and transmits it to the ROS2 distributed control module;

[0023] The navigation control node in the ROS2 distributed control module generates a U-shaped reference path based on the preset operating area. The motion control node subscribes to positioning data, heading angle information, and the reference path. Using a model-predictive motion control algorithm, it calculates the speed difference between the ducted fans on both sides of the dual-ducted propulsion system and outputs PWM instructions to the electronic speed regulator, enabling real-time adjustment of heading and speed.

[0024] When the hull is in motion, the weeding execution module arranged on the hull performs weeding operations.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system of the present invention overcomes the technical difficulties of poor shallow water adaptability, low positioning accuracy and high crop damage rate of traditional paddy field weeding equipment, providing efficient and reliable technical support for paddy field precision agriculture. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a structural schematic diagram of the RTK paddy field weeding unmanned boat based on the ROS2 robot operating system of the present invention.

[0028] Figure 2 Schematic diagram of the parametric hull model.

[0029] Figure 3 This is a Gazebo simulation diagram.

[0030] Figure 4 This is an architectural diagram of the control system of the RTK paddy field weeding unmanned boat based on the ROS2 robot operating system of the present invention.

[0031] Figure 5 This is an architectural diagram of the control method of the RTK paddy field weeding unmanned boat based on the ROS2 robot operating system of the present invention.

[0032] Figure 6 This is a simulation diagram of the model predictive motion control (MPC) algorithm in Example 2.

[0033] In the figure: 1-hull; 2-ducted fan; 3-chain. DETAILED DESCRIPTION

[0034] The present invention will be described in further detail below with reference to the embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0035] Example 1

[0036] See also Figure 1 The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system of the present invention includes a hull, an RTK positioning and orientation module, a weeding execution module, a power drive module, a ROS2 distributed control module, a power supply module and an emergency remote control module.

[0037] See also Figure 1 The hull is made of aluminum alloy and adopts a flat-bottom streamlined design. Through the above configuration, the hull can be adapted to shallow water environments such as paddy fields. By eliminating traditional steering mechanisms such as rudders on the hull, entanglement of rice roots can be avoided. By differentially controlling the dual-ducted propellers to achieve flexible steering of the hull, the draft of the hull can be significantly reduced.

[0038] In addition, a sealed cabin is provided inside the hull for installing the ROS2 distributed control module, the RTK positioning and orientation module and the power supply module to ensure that the RTK paddy field weeding unmanned boat of the present invention can operate stably in a humid environment.

[0039] See also Figure 1 The RTK positioning and orientation module combines dual-antenna space vector solution technology to provide centimeter-level positioning data and heading angle information in real time, including a ground base station and a mobile station set on the hull, wherein the ground base station is installed on a fixed pile at the edge of the paddy field, receives satellite signals through a high-gain antenna and a multi-frequency GNSS module, and uses a data radio to send differential data to the mobile station; the mobile station is deployed in a sealed cabin of the hull, constructs a space baseline vector through a dual helix antenna, uses space vector solution technology to solve the received differential data, outputs centimeter-level positioning data and heading angle information in real time, and transmits it to the ROS2 distributed control module through serial communication.

[0040] Before starting work, the system will self-check whether each functional module is online normally. During the working process, the GNSS module will also continuously self-check. If the base station signal is unstable, it will switch the positioning mode to use only GNSS positioning; that is, during normal operation, RTK mode takes priority, and if the signal is lost, it will switch to GNSS single point positioning.

[0041] See also Figure 1 The power drive module includes a dual-ducted propeller and an electronic speed governor provided on the hull, wherein the electronic speed governor controls the steering of the hull by adjusting the speed difference between the ducted fans on both sides of the dual-ducted propeller and dynamically adjusts the steering response in combination with real-time positioning data;

[0042] In this embodiment, the power drive module uses dual 64mm brushless ducted propellers to form a differential steering system, which is independently controlled by two Feiying Jiale brushless electronic speed controllers (continuous current 90A). Among them, the dual 64mm brushless ducted propellers use 2840-KV3150 brushless motors with 11-blade propeller structures, which can generate 1150g thrust at a working voltage of 16.5V.

[0043] See also Figure 1 The ROS2 distributed control module includes a navigation control node, a motion control node and a GNSS data acquisition node, wherein:

[0044] The navigation control node uses a line of sight (LOS) algorithm to generate a reference path according to a preset operation area;

[0045] The motion control node performs real-time rolling optimization on the motion state of the hull based on the model predictive motion control (MPC) algorithm, and calculates the thrust values ​​required by the ducted fans on both sides of the dual-ducted propulsion system.

[0046] The GNSS data acquisition node is used to obtain positioning data in real time, and encapsulates the data into a standard message format through the ROS2 topic communication mechanism, and publishes it to the system bus for other subscribing nodes to obtain in real time;

[0047] See also Figure 1 The weeding execution module is composed of multiple chains; the multiple chains are arranged in parallel along the width direction of the hull; one end of each chain is fixed to the stern of the hull through a connecting member (the connecting member includes a hook set on the chain and an interface set on the hull), and the other end is provided with a counterweight block; during the movement of the hull, the chain set on the hull and with a counterweight block at the end is subjected to the action of the water flow to swing periodically, thereby disturbing the bottom sediment and destroying the weed root system to complete the weeding operation, while also avoiding damage to the rice seedlings;

[0048] In this embodiment, the chain is made of engineering plastic, and the width and length of a single section of the chain are 25mm×50mm; the size of the counterweight block is 50mm×30mm×10mm, and the counterweight block is connected to the end of the chain through a 304 stainless steel ring.

[0049] See also Figure 1 The dual-channel fault-tolerant detection system includes an external link monitoring node and a health monitoring node. The external link monitoring node is used to verify the frame header and frame tail of the SBUS protocol in real time. When 5 consecutive frames of invalid data are detected, the fail-safe protection is triggered and an emergency stop command is sent to the hardware enable end of the power drive module. The health monitoring node is used to verify the loading status of all functional nodes when the system is started, detect the survival status of each functional node at a frequency of 10Hz during operation, and immediately stop the current operation task when any functional node is offline.

[0050] See also Figure 1 , the emergency remote control module includes a handheld remote control and an SBUS receiver, wherein,

[0051] The handheld remote control is equipped with a three-position switch (manual / automatic / emergency stop); wherein,

[0052] Manual mode: Navigation is completely controlled by the handheld remote control;

[0053] Automatic mode: execute the preset operation program;

[0054] Emergency stop mode: immediately cut off the power supply;

[0055] The SBUS receiver is used to receive remote control signals in real time.

[0056] See also Figure 1 The power module is used to power the RTK positioning and orientation module, the weeding execution module, the power drive module and the ROS2 distributed control module. The power module integrates overvoltage protection, reverse connection protection and multi-channel voltage conversion functions to support the stable operation of various functional modules in the system.

[0057] In this embodiment, the power module uses a 4S lithium polymer battery pack (16.8V / 16000mAh) as the energy core, and is connected to a multi-layer PCB power adapter board through an XT60 interface. The multi-layer PCB power adapter board uses an RT8289GSP chip to achieve a 5V / 3A regulated output; the multi-layer PCB power adapter board is configured with a P6SMB550A module to build a three-level protection system for overvoltage, overcurrent, and reverse connection. The signal interface of the multi-layer PCB power adapter board uses a GH1.25 waterproof connector to integrate remote control reception, sensor bus, and PWM control circuits.

[0058] See also Figure 1 The control method of the RTK paddy field weeding unmanned boat based on the ROS2 robot operating system of the present invention comprises the following steps:

[0059] The ground base station receives satellite signals and uses a data transmission radio to send differential data to the mobile station; the mobile station processes the received differential data, outputs positioning data and heading angle information, and transmits it to the ROS2 distributed control module;

[0060] The navigation control node generates a U-shaped reference path based on the preset operation area. The interval between the path points of the reference path is dynamically adjusted based on the actual size of the paddy field.

[0061] The motion control node subscribes to positioning data, heading angle information, and reference path, calculates the speed difference between the ducted fans on both sides of the dual-ducted propulsor through the model predictive motion control (MPC) algorithm, and outputs PWM instructions to the electronic speed regulator to achieve real-time adjustment of heading and speed.

[0062] During the movement of the hull, the chain with a counterweight at the end is set on the hull and swings periodically under the action of the water flow, disturbing the bottom sediment and destroying the weed roots to complete the weeding operation.

[0063] During the above process, the power module monitors the voltage status in real time and triggers the protection mechanism to prevent overvoltage or reverse connection failures; the ROS2 distributed control module ensures the reliable transmission of control instructions through redundant communication.

[0064] In this embodiment, the line-of-sight (LOS) algorithm and the model predictive motion control (MPC) algorithm can be implemented using existing methods.

[0065] Example 2

[0066] See also Figure 2-Figure 6 The difference between this embodiment and embodiment 1 is that the model predictive motion control (MPC) algorithm includes the following steps:

[0067] Step S1: Based on Fossen's classic ship dynamics and kinematics model, a dynamics and kinematics model of a double-ducted fan driven paddy field unmanned vessel is constructed in a paddy field scenario. The specific steps are as follows:

[0068] S101: Use SolidWorks to build a parametric hull model and perform fluid simulation on the parametric hull model (such as Figure 3 As shown), obtain simulation data;

[0069] S102: Constructing an unmanned vessel with the same parameterized hull model as in step S101, and performing a towing test on the unmanned vessel to measure the resistance of the unmanned vessel at a water depth of 0.05 m. A tension and compression sensor with an accuracy of 0.1 kg is used in the towing test, and Kalman filtering is performed on the obtained experimental data.

[0070] S103: Combine simulation data with experimental data and use the least squares method to identify and simplify the parameters of the parametric hull model;

[0071] S104: Based on the parameters obtained in step S103, a dynamic and kinematic model of the unmanned paddy field boat driven by a double-ducted fan is constructed, wherein:

[0072] The kinematic model is:

[0073]

[0074] Where: η = [x, y, ψ]′ represents the displacement angle vector, which is used to represent the position and direction information of the unmanned ship in the fixed coordinate system; represents the transformation matrix; v = [u, v, r]′ represents the velocity vector, which is used to represent the speed of the unmanned ship in the plane;

[0075] The kinetic model is:

[0076]

[0077] Where: M represents the inertia matrix; C(v) represents the Coriolis force-centripetal force matrix. However, in this control method, since the unmanned ship is at a low speed and has a light mass, it can be ignored. D(v) is the damping matrix, which is used to represent the environmental resistance characteristics of the unmanned ship during operation. In this control method, since the unmanned ship is at a low speed, only the linear term is retained. τ = [U1 + U2, 0, (U1 - U2) * L] is the resultant thrust of the two ducted fans of the unmanned ship.

[0078] Step S2: Improve the line-of-sight (LOS) algorithm and construct a guidance module for the dual-drive unmanned boat suitable for paddy field environments. The specific steps are as follows:

[0079] S201: Uses RTK positioning and orientation module (accuracy ±1cm) to obtain the transplanting trajectory, with a sampling frequency of 10Hz;

[0080] S202: Generate an operation area using polygonal Boolean operations, where the retraction distance d = 0.3 × operation width + safety factor (valued at 0.2), and the retraction distance needs to be determined based on the width of the weeding execution module carried on the unmanned vessel.

[0081] Step S3: Based on the dynamics and kinematics model and guidance module of the dual-ducted fan-driven paddy field unmanned boat, a hierarchical model predictive (MPC) controller is constructed and solved to obtain the thrust values ​​required by the two ducted fans in the unmanned boat. The specific steps are as follows:

[0082] S301: Define the state space matrix and the control input matrix, where:

[0083] The state space matrix is ​​X = [x, y, ψ, u, v, r]′; the control input matrix is ​​f = [U1, U2]′; where U1 and U2 are the thrust of the left and right duct fans of the UAV (constrained by F_max); and v is the lateral velocity, which is calculated by decoupling the dynamic equations.

[0084] S302: Constructing a hierarchical optimization variable matrix; the hierarchical optimization variable matrix includes a control sequence matrix F∈R∧{N×2} (N=horizon) and a state sequence matrix X∈R∧{N+1×6};

[0085] S303: Establish system constraints based on actual physical conditions, including:

[0086] Initial state constraints:

[0087] X[0,:]=state;

[0088] Dynamic recursive constraints (loop construction):

[0089]

[0090] Enter hard constraints:

[0091] ||F[k]||≤F_max;

[0092] Heading angle error constraint:

[0093] ||Δθ||≤π;

[0094] S304: Construct an objective function for multi-objective optimization, wherein the constructed objective function is:

[0095] cost=∑[0.1*Δu 2 +1*Δθ 2 +0.1||F[k]|| 2 ];

[0096] The weight of the first term is used to reduce the speed error, the weight of the second term is used to reduce the heading angle error, and the weight of the third term is used to smooth the motor output;

[0097] S4: CVXPY is used to solve the objective function in real time to obtain the thrust values ​​required by the two ducted fans, specifically:

[0098] According to the objective function, CVXPY is used to construct the quadratic programming problem min(Fcost);

[0099] In satisfaction Under the premise of , the quadratic programming problem min(Fcost) is solved.

[0100] In addition, during the solution process, an exception handling mechanism is introduced, which includes solution failure detection and model mismatch compensation.

[0101] The solution failure detection is as follows: if a solution failure occurs, the control output of the previous prediction time step is adopted;

[0102] The model mismatch compensation is to estimate the unmodeled disturbance by extending the state observer, and to correct the predicted trajectory based on the estimated disturbance.

[0103] Finally, a hardware-in-the-loop simulation platform was built and verified in the joint environment of VSCODE and ROS / Gazebo to compare the performance of the PID controller, LQR controller, and the MPC controller of the present invention. The specific steps are as follows:

[0104] like Figure 6 As shown, a circular desired trajectory is constructed; the tracking effects of the unmanned ship under the control of PID controller, LQR controller and MPC controller are compared, including but not limited to heading angle error and speed error;

[0105] Experimental results show that the lateral tracking error of the unmanned boat controlled by the MPC controller in the present invention is reduced by 42% (RMSE ≤ 0.08m) at an operating speed of 1m / s compared with traditional methods (PID controller, LQR controller), and meets the requirements of 20Hz real-time control. It is suitable for high-coverage and high-maneuverability unmanned boat operation scenarios in shallow water environments of rice fields.

[0106] The present invention proposes a dual closed-loop control method that integrates an improved LOS guidance law with a model predictive motion control (MPC) algorithm. By establishing a simplified dynamic model suitable for shallow water dual-drive scenarios, the secondary resistance term is ignored and the thrust distribution strategy is optimized. An improved LOS guidance law with dynamic curvature constraints is designed, and the dynamic window method is combined to achieve smooth tracking of large curvature paths. A real-time controller based on the model predictive motion control (MPC) algorithm is further constructed. The state space order reduction model and the rolling horizon optimization algorithm are used to compress the single-step calculation time to less than 5ms while ensuring control accuracy.

[0107] The above is a preferred embodiment of the present invention, but the embodiment of the present invention is not limited to the above content. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. An RTK paddy field weeding unmanned boat based on the ROS2 robot operating system, characterized in that: It includes hull, RTK positioning and orientation module, weeding execution module, power drive module, ROS2 distributed control module, power supply module and emergency remote control module, among which, The RTK positioning and orientation module includes a ground base station and a mobile station installed on the hull, wherein the ground base station is used to receive satellite signals and send differential data to the mobile station using a data radio; the mobile station processes the received differential data, outputs positioning data and heading angle information, and transmits it to the ROS2 distributed control module; The power drive module includes a dual-ducted propeller and an electronic speed governor provided on the hull, wherein the electronic speed governor controls the steering of the hull by adjusting the speed difference between the ducted fans on both sides of the dual-ducted propeller and dynamically adjusts the steering response in combination with real-time positioning data; The ROS2 distributed control module includes a navigation control node, a motion control node, a GNSS data acquisition node and a dual-channel fault-tolerant detection system, wherein the navigation control node is used to generate a reference path according to a preset operating area; the motion control node is used to optimize the control instructions of the dual-duct propulsion system; the GNSS data acquisition node is used to obtain positioning data in real time, and encapsulate the data into a standard message format through the ROS2 topic communication mechanism, and publish it to the system bus for other subscribing nodes to obtain in real time; the dual-channel fault-tolerant detection system includes an external link monitoring node and a health monitoring node, wherein the external link monitoring node is used to verify the frame header and frame tail of the SBUS protocol in real time, trigger the out-of-control protection when 5 consecutive frames of invalid data are detected, and send an emergency stop command to the hardware enable end of the power drive module; the health monitoring node is used to verify the loading status of all functional nodes when the system starts, detect the survival status of each functional node at a frequency of 10Hz during operation, and immediately stop the current operation task when any functional node is offline; The power supply module is used to supply power to each functional module.

2. The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system according to claim 1 is characterized in that: The hull is made of aluminum alloy and has a flat bottom streamlined design.

3. The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system according to claim 2 is characterized in that: The ground base station receives satellite signals through a high-gain antenna and a multi-frequency GNSS module, and uses a data transmission radio to send differential data to the mobile station.

4. The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system according to claim 3 is characterized in that: The mobile station is deployed in the cabin of the hull, constructs a space baseline vector through a double helix antenna, and uses space vector solution technology to solve the received differential data, outputs positioning data and heading angle information in real time, and transmits it to the ROS2 distributed control module through serial communication.

5. The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system according to claim 4 is characterized in that: The navigation control node generates a reference path using a line-of-sight guidance algorithm.

6. The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system according to claim 5 is characterized in that: The motion control node performs real-time rolling optimization on the motion state of the unmanned ship based on a model-predictive motion control algorithm, and calculates the thrust values ​​required by the ducted fans on both sides of the dual-ducted propeller.

7. The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system according to claim 6 is characterized in that: The weeding execution module is composed of multiple chains; the multiple chains are arranged in parallel along the width direction of the hull; one end of each chain is fixed to the stern through a connecting piece, and the other end is provided with a counterweight block.

8. The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system according to claim 7 is characterized in that: The power supply module includes a power supply module, a voltage conversion module and a protection module.

9. The RTK paddy field weeding unmanned boat based on the ROS2 robot operating system according to claim 1, characterized in that: The emergency remote control module includes a handheld remote control and an SBUS receiver, wherein the handheld remote control is equipped with a three-position switch corresponding to manual mode, automatic mode and emergency stop mode; the SBUS receiver is used to receive remote control signals in real time.

10. A control method for the RTK paddy field weeding unmanned boat based on the ROS2 robot operating system according to any one of claims 1 to 9, characterized in that: The following steps are involved: The ground base station receives satellite signals and uses a data transmission radio to send differential data to the mobile station; the mobile station processes the received differential data, outputs positioning data and heading angle information, and transmits it to the ROS2 distributed control module; The navigation control node in the ROS2 distributed control module generates a U-shaped reference path based on the preset operation area; The motion control node subscribes to positioning data, heading angle information, and reference path, calculates the speed difference between the ducted fans on both sides of the dual-ducted propulsor through a model-predictive motion control algorithm, and outputs PWM instructions to the electronic speed regulator to achieve real-time adjustment of heading and speed. When the hull is in motion, the weeding execution module arranged on the hull performs weeding operations.

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